Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Genomics02:02

Genomics

40.4K
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
40.4K
Genomic Imprinting and Inheritance02:30

Genomic Imprinting and Inheritance

37.1K
Diploid organisms inherit genetic material through chromosomes from both parents. Copies of the same gene are known as alleles. In most cases, both alleles are simultaneously expressed and allow various cellular processes to function optimally. If one of the alleles is missing or mutated, the expression of the other allele can compensate; however, this is not true for all genes.
The expression of some genes depends on which parent passed the gene to the offspring, through a phenomenon known as...
37.1K
Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

9.1K
While every living organism has a genome of some kind (be it RNA, or DNA), there is considerable variation in the sizes of these blueprints. One major factor that impacts genome size is whether the organism is prokaryotic or eukaryotic. In prokaryotes, the genome contains little to no non-coding sequence, such that genes are tightly clustered in groups or operons sequentially along the chromosome. Conversely, the genes in eukaryotes are punctuated by long stretches of non-coding sequence.
9.1K
Cis-regulatory Sequences02:02

Cis-regulatory Sequences

11.8K
Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
11.8K
Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes02:16

Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes

15.9K
The present-day mitochondrial and chloroplast genomes have retained some of the characteristics of their ancestral prokaryotes and also have acquired new attributes during their evolution within eukaryotic cells. Like prokaryotic genomes, mitochondrial and chloroplast genomes neither bind with histone-like proteins nor show complex packaging into chromosome-like structures, as observed in eukaryotes. Unlike mitotic cell divisions observed in eukaryotic cells, mitochondria and chloroplasts...
15.9K
How Data are Classified: Categorical Data01:11

How Data are Classified: Categorical Data

44.2K
A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
44.2K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A rare missense variant impacting NEK1 kinase function is associated with ALS.

Acta neuropathologica communications·2026
Same author

A kinetics-based model of haematopoiesis reveals extrinsic regulation of skewed lineage output from stem cells.

Nature cell biology·2026
Same author

Glucocorticoids induce a phagocytic C1Q+ macrophage phenotype primed for IFNγ-dependent CXCL9 secretion.

Scientific reports·2026
Same author

Natural killer cell immunotherapy reverses lung fibrosis by eliminating senescent fibroblasts.

Science translational medicine·2026
Same author

Clinically actionable genomic and transcriptomic landscape of advanced neuroendocrine neoplasms.

Med (New York, N.Y.)·2026
Same author

The spectrum of immunoglobulin heavy chain enhancer hijacking in chronic lymphocytic leukemia.

Leukemia·2026

Related Experiment Video

Updated: Jan 29, 2026

Ultra-long Read Sequencing for Whole Genomic DNA Analysis
10:34

Ultra-long Read Sequencing for Whole Genomic DNA Analysis

Published on: March 15, 2019

24.0K

Evaluation of Whole Genome Sequencing Data.

Daniel Hübschmann1,2,3, Matthias Schlesner4

  • 1Division of Theoretical Bioinformatics (B080), German Cancer Research Center (DKFZ), Heidelberg, Germany.

Methods in Molecular Biology (Clifton, N.J.)
|February 20, 2019
PubMed
Summary

Whole genome sequencing (WGS) offers deep insights into lymphoma genetics. This study details WGS data analysis methods, including variant identification and quality control, crucial for understanding lymphoma.

Keywords:
Mutational signaturesNext-generation sequencingQuality controlVariant calling

More Related Videos

Novel Sequence Discovery by Subtractive Genomics
09:40

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

9.1K
Genomic MRI - a Public Resource for Studying Sequence Patterns within Genomic DNA
12:36

Genomic MRI - a Public Resource for Studying Sequence Patterns within Genomic DNA

Published on: May 9, 2011

10.6K

Related Experiment Videos

Last Updated: Jan 29, 2026

Ultra-long Read Sequencing for Whole Genomic DNA Analysis
10:34

Ultra-long Read Sequencing for Whole Genomic DNA Analysis

Published on: March 15, 2019

24.0K
Novel Sequence Discovery by Subtractive Genomics
09:40

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

9.1K
Genomic MRI - a Public Resource for Studying Sequence Patterns within Genomic DNA
12:36

Genomic MRI - a Public Resource for Studying Sequence Patterns within Genomic DNA

Published on: May 9, 2011

10.6K

Area of Science:

  • Genomics
  • Oncology
  • Bioinformatics

Background:

  • Lymphomas are cancers of the lymphatic system with complex genetic underpinnings.
  • Whole genome sequencing (WGS) is a powerful tool for comprehensively analyzing the genetic alterations in lymphomas.

Purpose of the Study:

  • To describe methods for analyzing whole genome sequencing (WGS) data in lymphoma.
  • To guide the design and quality control of WGS studies for lymphoma research.

Main Methods:

  • Alignment of WGS reads to a reference genome.
  • Identification and classification of various genomic variants (e.g., SNPs, indels, structural variants).
  • Detection of driver mutations and mutational signatures.
  • Quality control metrics for assessing WGS data integrity.

Main Results:

  • Established a workflow for comprehensive WGS data analysis in lymphomas.
  • Detailed methods for variant calling, driver mutation identification, and mutational signature analysis.
  • Provided guidelines for WGS study design and quality assurance.

Conclusions:

  • WGS analysis provides a detailed view of lymphoma genomes.
  • Standardized methods and quality control are essential for reliable WGS data interpretation in lymphoma.
  • This work facilitates deeper understanding of lymphoma pathogenesis through genomic analysis.